Search Results (44)

During the adaptive evolution of animals, the host and its gut microbiota co-adapt to different elevations. Currently, there are few reports on the rumen microbiota–hepato-intestinal axis of Tibetan sheep at different altitudes. Therefore, the purpose of this study was to explore the regulatory effect of rumen microorganism–volatile fatty acids (VFAs)–VFAs transporter gene interactions on the key enzymes and genes related to gluconeogenesis in Tibetan sheep. The rumen fermentation parameters, rumen microbial densities, liver gluconeogenesis activity and related genes were determined and analyzed using gas chromatography, RT-qPCR and other research methods. Correlation analysis revealed a reciprocal relationship among rumen microflora–VFAs-hepatic gluconeogenesis in Tibetan sheep at different altitudes. Among the microbiota, Ruminococcus flavefaciens (R. flavefaciens), Ruminococcus albus (R. albus), Fibrobactersuccinogenes and Ruminobacter amylophilus (R. amylophilus) were significantly correlated with propionic acid (p < 0.05), while propionic acid was significantly correlated with the transport genes monocarboxylate transporter 4 (MCT4) and anion exchanger 2 (AE2) (p < 0.05). Propionic acid was significantly correlated with key enzymes such as pyruvate carboxylase, phosphoenolpyruvic acid carboxylase and glucose (Glu) in the gluconeogenesis pathway (p < 0.05). Additionally, the expressions of these genes were significantly correlated with those of the related genes, namely, forkhead box protein O1 (FOXO1) and mitochondrial phosphoenolpyruvate carboxykinase 2 (PCK2) (p < 0.05). The results showed that rumen microbiota densities differed at different altitudes, and the metabolically produced VFA contents differed, which led to adaptive changes in the key enzyme activities of gluconeogenesis and the expressions of related genes. Full article

Exosomes, nanoscale vesicles derived from human cells, offer great promise for targeted drug delivery. However, their inherent diversity and genetic modifications present challenges in terms of ensuring quality in clinical use. To explore solutions, we employed advanced gene fusion and transfection techniques in human 293T cells to generate two distinct sets of genetically engineered samples. We used dual-omics analysis, combining transcriptomics and proteomics, to comprehensively assess exosome quality by comparing with controls. Transcriptomic profiling showed increased levels of engineering scaffolds in the modified groups, confirming the success of genetic manipulation. Through transcriptomic analysis, we identified 15 RNA species, including 2008 miRNAs and 13,897 mRNAs, loaded onto exosomes, with no significant differences in miRNA or mRNA levels between the control and engineered exosomes. Proteomics analysis identified changes introduced through genetic engineering and over 1330 endogenous exosome-associated proteins, indicating the complex nature of the samples. Further pathway analysis showed enrichment in a small subset of cellular signaling pathways, aiding in our understanding of the potential biological impacts on recipient cells. Detection of over 100 cow proteins highlighted the effectiveness of LC-MS for identifying potential contaminants. Our findings establish a dual-omics framework for the quality control of engineered exosome products, facilitating their clinical translation and therapeutic applications in nanomedicine. Full article

In order to address the fragility issues associated with the current prescribed performance control (PPC) strategy and ensure both transient and steady-state performance of the tracking error, a non-fragility prescribed performance control scheme is proposed. A non-fragile prescribed performance control method for robotic systems with model uncertainties and unknown disturbances is developed. This method not only addresses the inherent vulnerability defects of the existing prescribed performance control but also effectively reduces the computational complexity of the controller. Firstly, addressing the fragility issues of existing PPC, a new non-fragile prescribed performance control strategy is proposed. To address the fragile issue with the current PPC, the shift function is employed to handle the tracking error. Based on the non-fragile PPC mentioned above, a new prescribed performance controller is designed without the requirement for approximation or estimation. This effectively reduces the complexity of controller design. At last, the feasibility of achieving non-fragile prescribed performance is verified through stability analysis, and the superiority of the designed controller is confirmed through simulation comparisons. The results show that the designed controller effectively resolves the control singularity issue arising from the inherent limitations of the PPC. Full article

The gut microbiota is highly symbiotic with the host, and the microbiota and its metabolites are essential for regulating host health and physiological functions. Astragalus, as a feed additive, can improve animal immunity. However, the effects of Astragalus root powder on the rumen microbiota and their metabolites in lambs are not apparent. In this study, thirty healthy Hu sheep lambs with similar body weights (17.42 ± 2.02 kg) were randomly selected for the feeding experiment. Lambs were fed diets supplemented with 0.3% Astragalus root powder, and the rumen microbiota density and metabolome were measured to determine the effects of Astragalus on the health of lambs in the rumen. The results showed that the relative abundance of Butyrivibrio fibrisolvens (Bf), Ruminococcus flavefaciens (Rf), Succiniclasticum (Su), and Prevotella (Pr) in the rumen was increased in the Astragalus group (p < 0.01), and metabolic profiling showed that the metabolites, such as L-lyrosine and L-leucine, were upregulated in the Astragalus group (p < 0.01). KEGG functional annotation revealed that upregulated metabolites were mainly enriched in the pathways of amino acid metabolism, lipid metabolism, fatty acid biosynthesis, and bile secretion in the Astragalus group, and downregulated metabolites were enriched in the pathways of methane metabolism and other pathways. Correlation analysis revealed that butyric acid was positively correlated with Roseburia and Blautia (p < 0.05) and negatively correlated with Desulfovibrio (p < 0.05). Thus, by analyzing the interactions of Astragalus root powder with the density of rumen microorganisms and their metabolites in lambs, it was shown that Astragalus root powder could improve the structure of rumen microbiota and their metabolites and then participate in the regulation of amino acid metabolism, lipid metabolism, immune metabolism, and other pathways to improve the efficiency of energy absorption of the lambs. Full article

The gecko can achieve flexible climbing on various vertical walls and even ceilings, which is closely related to its unique foot adhesion system. In the past two decades, the mechanism of the gecko adhesion system has been studied in-depth, and a verity of gecko-inspired adhesives have been proposed. In addition to its strong adhesion, its easy detachment is also the key to achieving efficient climbing locomotion for geckos. A similar controllable adhesion characteristic is also key to the research into artificial gecko-inspired adhesives. In this paper, the structures, fabrication methods, and applications of gecko-inspired controllable adhesives are summarized for future reference in adhesive development. Firstly, the controllable adhesion mechanism of geckos is introduced. Then, the control mechanism, adhesion performance, and preparation methods of gecko-inspired controllable adhesives are described. Subsequently, various successful applications of gecko-inspired controllable adhesives are presented. Finally, future challenges and opportunities to develop gecko-inspired controllable adhesive are presented. Full article

The intestinal microbiota of ruminants is an important factor affecting animal production and health. Research on the association mechanism between the intestinal microbiota and meat quality of ruminants will play a positive role in understanding the formation mechanism of meat quality in ruminants and improving production efficiency. In this study, the fatty acid composition and content, expression of related genes, and structural characteristics of the ileum microbiota of ewes of Tibetan sheep at different ages (4 months, 1.5 years, 3.5 years, and 6 years) were detected and analyzed. The results revealed significant differences in fatty acid composition and content in the muscle of Tibetan sheep at different ages (p < 0.05); in addition, the content of MUFAs in the longissimus dorsi muscle and leg muscle was higher. Similarly, the expressions of muscle-related genes differed among the different age groups, and the expression of the LPL, SCD, and FABP4 genes was higher in the 1.5-year-old group. The ileum microbiota diversity was higher in the 1.5-year-old group, the Romboutsia abundance ratio was significantly higher in the 1.5-year-old group (p < 0.05), and there was a significant positive correlation with oleic acid (C18:1n9c) (p < 0.05). In conclusion, the content of beneficial fatty acids in the longissimus dorsi muscle and leg muscle of Tibetan sheep was higher at 1.5 years of age, and the best slaughter age was 1.5 years. This study provides a reference for in-depth research on the mechanism of the influence of the gut microbiota on meat quality and related regulation. Full article

To solve problems in dissimilarly light metal joints, refilled friction stir spot welding (RFSSW) is proposed instead of resistance spot welding. However, rotation speed, dwell time, plunge depth, and the diameter of welding tools all have a great influence on joints, which brings great challenges in optimizing welding parameters to ensure their mechanical properties. In this study, the 1.5 mm thick 2A12Al and 2 mm thick 7B04Al lap joints were prepared by Taguchi orthogonal experiment design and RFSSW. The welding tool (shoulder) diameters were 5 mm and 7 mm, respectively. The macro/microstructures of the cross-section, the geometrical characteristics of the effective welding depth (EWD), the stir zone area (SZA), and the stir zone volume (SZV) were characterized. The shear strength and failure mode of the lap joint were analyzed using an optical microscope. It was found that EWD, SZA, and SZV had a good correlation with tensile–shear force. The optimal welding parameters of 5 mm diameter joints are 1500 rpm of rotation speed, 2.5 mm of plunge depth, and 0 s of dwell time, which for 7 mm joints are 1200 rpm, 1.5 mm, and 2 s. The tensile–shear force of 5 mm and 7 mm joints welded with these optical parameters was 4965 N and 5920 N, respectively. At the same time, the 5 mm diameter joints had better strength and strength stability. Full article

With the passage of time during pipeline operation, a substantial number of impurities accumulate and adhere to the inner wall of the pipeline. This deposition hinders the pipeline’s ability to function correctly, thereby posing significant hidden risks to people’s lives and the safety of their property. This article focuses on employing pipeline robots for internal cleaning. It examines the jet cleaning process of the spiral-driven pipeline inspection and cleaning robot, aiming to determine the optimal motion state and cleaning parameters for the device within the pipeline. The findings are verified and analyzed through experiments. It was observed that the cleaning effect is enhanced, with a target surface distance of approximately 12- to 13-times the diameter of the nozzle outlet (around 25 mm). In addition, an incident angle of 15° yields favorable cleaning results, with a maximum shear force exerted on the target surface of approximately 0.11 MPa. Ensuring that the pipelines operate reasonably and stably, thus guaranteeing their safe functioning and preventing significant economic and environmental damage, holds immense value. Full article

In order to clarify the magnetic-thermal-force changing rule of high-frequency transformers under different winding arrangements, this paper tests the magnetization and loss characteristics of nanocrystalline materials at different temperatures, and based on the magnetization and loss data, establishes a magnetic-thermal-force coupling calculation model of 15 kVA, 5 kHz nanocrystalline high-frequency transformers, and calculates and analyzes the magnetic flux density, loss and temperature rise distributions of high-frequency transformers with three different winding arrangements under no-load and short-circuit conditions, respectively. Through comparative analysis, it was found that under no-load conditions, the cross-transposition of winding has less influence on the magnetic flux of the high-frequency transformer core, but it can reduce the iron-core loss and transformer temperature rise. The cross-transposition of winding under short-circuit conditions can significantly reduce the leakage magnetic field strength of high-frequency transformers; complete cross-transposition weakens the high-frequency transformer losses and temperature rise better than partial cross-transposition. According to the winding current density and core leakage field distribution under short-circuit conditions, we calculated and analyzed the distribution of its the axial and radial electromagnetic forces. The results show that the axial electromagnetic force causes the winding to be squeezed from both ends to the middle, the radial electromagnetic force causes the primary winding to shrink inward and the secondary winding to expand outward, so cross-transposition can greatly reduce electromagnetic force and weakening the deformation of the winding. Therefore, high-frequency transformers of winding cross-transposed should be used in actual projects to reduce transformer temperature rise and improve efficiency and security. This research has theoretical significance for the multi-physical field coupling of high-frequency transformers and its structural design. Full article

In order to investigate the geographical distribution of forest fire occurrences in the Ningxia Hui Autonomous Region, this study employs advanced modeling techniques, utilizing diverse data sources, including fuel, Gross Domestic Product (GDP), population, meteorology, buildings, and grid data. This study integrates deep learning Convolutional Neural Networks (CNNs) to predict potential fire incidents. The research findings can be summarized as follows: (i) The employed model exhibits very good performance, achieving an accuracy of 84.35%, a recall of 86.21%, and an Area Under the Curve (AUC) of 87.67%. The application of this model significantly enhances the reliability of the forest fire occurrence model and provides a more precise assessment of its uncertainty. (ii) Spatial analysis shows that the risk of fire occurrence in most areas is low-medium, while high-risk areas are mainly concentrated in Longde County, Jingyuan County, Pengyang County, Xiji County, Yuanzhou District, Tongxin County, Xixia District, and Yinchuan City, which are mostly located in the southern, southeastern, and northwestern regions of Ningxia Hui Autonomous Region, with a total area of 2191.2 square kilometers. This underscores the urgent need to strengthen early warning systems and effective fire prevention and control strategies in these regions. The contributions of this research include the following: (i) The development of a highly accurate and practical provincial-level forest fire occurrence prediction framework based on grid data and deep learning CNN technology. (ii) The execution of a comprehensive forest fire prediction study in the Ningxia Hui Autonomous Region, China, incorporating multi-source data, providing valuable data references, and decision support for forest fire prevention and control. (iii) The initiation of a preliminary systematic investigation and zoning of forest fires in the Ningxia Hui Autonomous Region, along with tailored recommendations for prevention and control measures. Full article

Landslides pose significant and serious geological threat disasters worldwide, threatening human lives and property; China is particularly susceptible to these disasters. This paper focuses on Pengyang County, which is situated in the Ningxia Hui Autonomous Region of China, an area prone to landslides. This study investigated the application of machine learning techniques for analyzing landslide susceptibility. To construct and validate the model, we initially compiled a landslide inventory comprising 972 historical landslides and an equivalent number of non-landslide sites (Data sourced from the Pengyang County Department of Natural Resources). To ensure an impartial evaluation, both the landslide and non-landslide datasets were randomly divided into two sets using a 70/30 ratio. Next, we extracted 15 landslide conditioning factors, including the slope angle, elevation, profile curvature, plan curvature, slope aspect, TWI (topographic wetness index), TPI (topographic position index), distance to roads and rivers, NDVI (normalized difference vegetation index), rainfall, land use, lithology, SPI (stream power index), and STI (sediment transport index), from the spatial database. Subsequently, a correlation analysis between the conditioning factors and landslide occurrences was conducted using the certainty factor (CF) method. Three landslide models were established by employing logistic regression (LR), functional trees (FTs), and random subspace functional trees (RSFTs) algorithms. The landslide susceptibility map was categorized into five levels: very low, low, medium, high, and very high susceptibility. Finally, the predictive capability of the three algorithms was assessed using the area under the receiver operating characteristic curve (AUC). The better the prediction, the higher the AUC value. The results indicate that all three models are predictive and practical, with only minor discrepancies in accuracy. The integrated model (RSFT) displayed the highest predictive performance, achieving an AUC value of 0.844 for the training dataset and 0.837 for the validation dataset. This was followed by the LR model (0.811 for the training dataset and 0.814 for the validation dataset) and the FT model (0.776 for the training dataset and 0.760 for the validation dataset). The proposed methods and resulting landslide susceptibility map can assist researchers and local authorities in making informed decisions for future geohazard prevention and mitigation. Furthermore, they will prove valuable and be useful for other regions with similar geological characteristics features. Full article

Based on the serious phenomenon of Tibetan sheep “growing strong in warm seasons and losing weight in cold seasons”, this study explores the regulation of lncRNAs, microbiota, and metabolites in the cold season adaptation of Tibetan sheep from the perspective of the co-evolution of the host genome (first genome) and microbiome (second genome). RNA-seq results showed that 172 DE lncRNAs were identified in the rumen epithelium of Tibetan sheep in warm and cold seasons, of which 87 DE lncRNAs were significantly up-regulated in cold seasons. KEGG enrichment showed that target genes of up-regulated lncRNAs were significantly enriched in TNF signaling and oxidative phosphorylation pathways. LncRNA-mRNA regulatory network indicated that DE lncRNAs were involved in nutrient stress in the cold season by targeting ATP1B2, CADPS, TLR5, and UGT1A6. Correlation analysis showed some lncRNAs were significantly correlated with acetic acid, propionic acid, butyric acid, and rumen epithelial histomorphology and had a negative correlation with Butyrivibrio-2 and Succiniclasticum (p < 0.05). In addition, differential metabolites bilirubin and lncRNAs were co-enriched in the bile secretion pathway. lncRNAs played an important role in the adaptation process of Tibetan sheep in the cold season, and mediate the host to participate in nutrient absorption, energy utilization, and immune response, indicating that the host genome and microbial genome promote Tibetan sheep to adapt to nutrient stress in the cold season through co-evolution. Full article

Tibetan sheep are already well adapted to cold season nutrient stress on the Tibetan Plateau. Rumen, an important nutrient for metabolism and as an absorption organ in ruminants, plays a vital role in the cold stress adaptations of Tibetan sheep. Ruminal microbiota also plays an indispensable role in rumen function. In this study, combined multiomics data were utilized to comprehensively analyze the interaction mechanism between rumen epithelial miRNAs and microbiota and their metabolites in Tibetan sheep under nutrient stress in the cold season. A total of 949 miRNAs were identified in the rumen epithelium of both cold and warm seasons. A total of 62 differentially expressed (DE) miRNAs were screened using FC > 1.5 and p value < 0.01, and a total of 20,206 targeted genes were predicted by DE miRNAs. KEGG enrichment analysis revealed that DE miRNA-targeted genes were mainly enriched in axon guidance(ko04360), tight junction(ko04530), inflammatory mediator regulation of TRP channels(ko04750) and metabolism-related pathways. Correlation analysis revealed that rumen microbiota, rumen VFAs and DE miRNAs were all correlated. Further study revealed that the targeted genes of cold and warm season rumen epithelial DE miRNAs were coenriched with differential metabolites of microbiota in glycerophospholipid metabolism (ko00564), apoptosis (ko04210), inflammatory mediator regulation of TRP channels (ko04750), small cell lung cancer (ko05222), and choline metabolism in cancer (ko05231) pathways. There are several interactions between Tibetan sheep rumen epithelial miRNAs, rumen microbiota, and microbial metabolites, mainly through maintaining rumen epithelial barrier function and host homeostasis of choline and cholesterol, improving host immunity, and promoting energy metabolism pathways, thus enabling Tibetan sheep to effectively respond to cold season nutrient stress. The results also suggest that rumen microbiota have coevolved with their hosts to improve the adaptive capacity of Tibetan sheep to cold season nutrient stress, providing a new perspective for the study of cold season nutritional stress adaptation in Tibetan sheep. Full article

The invasive pest, Spodoptera frugiperda, commonly known as the fall armyworm (FAW), is a serious threat to food security in multiple countries worldwide. Insects’ antennal sensilla play a crucial role in perceiving plant odors and communication between male and female insects. This study aimed to examine the antennal morphology and sensilla variations on the antennae of FAW larvae and adults through scanning electron microscope analysis. The results revealed that third and fifth instar larval antennae possessed smell pores, sensilla pegs, and five types of antennal sensilla, namely sensilla trichodea, sensilla basiconica, sensilla chaetica, sensilla campaniform, and sensilla styloconicum, and the smell pores were first observed in Lepidoptera larvae. Furthermore, the size of sensilla in fifth instar larvae was significantly greater than those in third instar. On the adult antennae, there were smell pores and 12 types of sensilla identified: sensilla trichodea, sensilla basicaonica, sensilla auricillica, sensilla cavity, sensilla placodea, sensilla ligulate, Böhm’s bristles, sensilla chaetica, sensilla squamous, sensilla coeloconica, sensilla styloconicum, and sensilla uniporous peg. Notably, the sensilla cavity, sensilla placodea, sensilla ligulate, sensilla uniporous peg, and smell pores were first discovered in FAW adults. Compared with larvae, FAW adults have more types and amounts of sensilla. Additionally, we also discussed the possible functions of these antennal sensilla. This study provides valuable information for a comprehensive understanding of the type and function of antennal sensilla in FAW and assists in the development of novel pest control strategies, such as pest behavior control technology, for the prevention of this invasive pest. Full article

A full understanding of the patterns, trends, and strategies for long-term ecosystem changes helps decision-makers evaluate the effectiveness of ecological restoration projects. This study identified the ecological restoration approaches on planted forest, natural forest, and natural grassland protection during 2000–2022 based on a developed object-oriented continuous change detection and classification (OO-CCDC) method. Taking the Loess hilly region in the southern Ningxia Hui Autonomous Region, China as a case study, we assessed the ecological effects after protecting forest or grassland automatically and continuously by highlighting the location and change time of positive or negative effects. The results showed that the accuracy of ecological restoration approaches extraction was 90.73%, and the accuracies of the ecological restoration effects were 86.1% in time and 84.4% in space. A detailed evaluation from 2000 to 2022 demonstrated that positive effects peaked in 2013 (1262.69 km²), while the highest negative effects were observed in 2017 (54.54 km²). In total, 94.39% of the planted forests, 99.56% of the natural forest protection, and 62.36% of the grassland protection were in a stable pattern, and 35.37% of the natural grassland displayed positive effects, indicating a proactive role for forest management and ecological restoration in an ecologically fragile region. The negative effects accounted for a small proportion, only 2.41% of the planted forests concentrated in Pengyang County and 2.62% of the natural grassland protection mainly distributed around the farmland in the central-eastern part of the study area. By highlighting regions with positive effects as acceptable references and regions with negative effects as essential conservation objects, this study provides valuable insights for evaluating the effectiveness of the integrated ecological restoration pattern and determining the configuration of ecological restoration measures. Full article